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Author: Hubert Dichtl Publisher: ISBN: Category : Languages : en Pages : 53
Book Description
This study presents a systematic comparison of portfolio insurance strategies. In order to test for statistical significance of the differences in downside performance risk measures between pairs of portfolio insurance strategies, we use a bootstrap-based hypothesis test. Our comparison of different strategies considers the following distinguishing characteristics: static versus dynamic; initial wealth versus cumulated wealth protection; model-based versus model-free; and strong floor compliance versus probabilistic floor compliance. Our results show that the classical portfolio insurance strategies synthetic put and CPPI provide superior downside protection compared to a simple stop-loss trading rule, also resulting in significantly higher Omega ratios. Analyzing more recently developed strategies, neither the TIPP strategy (as an 'improved' CPPI strategy) nor the dynamic VaR-strategy provide significant improvements over the more traditional portfolio insurance strategies. The attractiveness of the dynamic VaR-strategy strongly depends on the quality of the estimates for the required input parameters, in particular, the equity risk premium. However, if an investor possesses superior forecasting skills, other active (market timing) strategies may exist which generate higher (risk-adjusted) returns compared to a protected passive stock market investment.
Author: Hubert Dichtl Publisher: ISBN: Category : Languages : en Pages : 53
Book Description
This study presents a systematic comparison of portfolio insurance strategies. In order to test for statistical significance of the differences in downside performance risk measures between pairs of portfolio insurance strategies, we use a bootstrap-based hypothesis test. Our comparison of different strategies considers the following distinguishing characteristics: static versus dynamic; initial wealth versus cumulated wealth protection; model-based versus model-free; and strong floor compliance versus probabilistic floor compliance. Our results show that the classical portfolio insurance strategies synthetic put and CPPI provide superior downside protection compared to a simple stop-loss trading rule, also resulting in significantly higher Omega ratios. Analyzing more recently developed strategies, neither the TIPP strategy (as an 'improved' CPPI strategy) nor the dynamic VaR-strategy provide significant improvements over the more traditional portfolio insurance strategies. The attractiveness of the dynamic VaR-strategy strongly depends on the quality of the estimates for the required input parameters, in particular, the equity risk premium. However, if an investor possesses superior forecasting skills, other active (market timing) strategies may exist which generate higher (risk-adjusted) returns compared to a protected passive stock market investment.
Author: Cheng-Few Lee Publisher: Springer Science & Business Media ISBN: 0387262849 Category : Business & Economics Languages : en Pages : 861
Book Description
This is a major new reference work covering all aspects of finance. Coverage includes finance (financial management, security analysis, portfolio management, financial markets and instruments, insurance, real estate, options and futures, international finance) and statistical applications in finance (applications in portfolio analysis, option pricing models and financial research). The project is designed to attract both an academic and professional market. It also has an international approach to ensure its maximum appeal. The Editors' wish is that the readers will find the encyclopedia to be an invaluable resource.
Author: Benjamin Hamidi Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
Controlling and managing potential losses is one of the main objective of the Risk Management. Following Ben Ameur and Prigent (2007) and Chen et al. (2008), and extending the first results by Hamidi et al. (2009) when adopting a risk management approach for defining insurance portfolio strategies, we analyze and illustrate a specific dynamic portfolio insurance strategy depending on the Value-at-Risk level of the covered portfolio on the French stock market. This dynamic approach is derived from the traditional and popular portfolio insurance strategy (Cf. Black and Jones, 1987; Black and Perold, 1992): the so-called "Constant Proportion Portfolio Insurance" (CPPI). However, financial results produced by this strategy crucially depend upon the leverage - called the multiple- likely guaranteeing a predetermined floor value whatever the plausible market evolutions. In other words, the unconditional multiple is defined once and for all in the traditional setting. The aim of this article is to further examine an alternative to the standard CPPI method, based on the determination of a conditional multiple. In this time-varying framework, the multiple is conditionally determined in order for the risk exposure to remain constant, even if it also depends upon market conditions. Furthermore, we propose to define the multiple as a function of an extended Dynamic AutoRegressive Quantile model of the Value-at-Risk (DARQ-VaR). Using a French daily stock database (CAC40 and individual stocks in the period 1998-2008), we present the main performance and risk results of the proposed Dynamic Proportion Portfolio Insurance strategy, first on real market data and secondly on artificial bootstrapped and surrogate data. Our main conclusion strengthens the previous ones: the conditional Dynamic Strategy with Constant-risk exposure dominates most of the time the traditional Constant-asset exposure unconditional strategies.
Author: Ralf Hohmann Publisher: GRIN Verlag ISBN: 334640868X Category : Business & Economics Languages : en Pages : 23
Book Description
Scientific Essay from the year 2021 in the subject Business economics - Investment and Finance, , language: English, abstract: Investments in money and capital markets involve different loss potentials that market participants should be able to manage. Below follows an overview and comparison of selected strategies to manage these risks. Portfolio insurance (PI) strategies were developed in the 1980s. They are used to hedge portfolios or individual investments against price losses. The volume of assets hedged with these strategies is significant. Different forms of individual strategies have developed over the years. Risk quantification and Value at Risk (VAR) strategies emerged around the same time. Risks of individual investments or portfolios were measured and different strategies were developed to take them into account in Value at Risk optimised portfolios (VaRoP). VaRoP is a strategy that calculates an optimal portfolio taking into account a given or permissible maximum VAR. Both strategies are intended to protect portfolios from losses in value. Their similarities and differences as well as their successes are presented and summarised in this paper. Their applicability in practice is also examined.
Author: Felix Lütjen Publisher: GRIN Verlag ISBN: 3668490163 Category : Business & Economics Languages : en Pages : 35
Book Description
Bachelor Thesis from the year 2016 in the subject Business economics - General, grade: 1.7, University of Frankfurt (Main), language: English, abstract: Risk aversion is a common trait among investors. While it is possible to reduce risk attributed to specific industries and regions by diversifying among different securities, market risk affects all securities on the market. Even a perfectly diversified portfolio is subject to systematic or market risk. It can be managed through diversification across asset classes, for example by shifting some of the funds invested into risk-free assets. For some investors, this yields unsatisfactory results as the expected return directly decreases linearly with an increase in the position in the risk-free asset. Portfolio insurance (PI) describes an alternative set of strategies that allows investors to reduce their exposure to market risk by guaranteeing the value of the portfolio to be above a certain value at the end of the investment period while allowing for participation in rising stock markets. Option-based portfolio insurance (OBPI) refers to a set of strategies in which either a conventional put option (protective put) or a replicated put option (synthetic put) is used to insure a portfolio against adverse price movements. In theory and assuming perfect market conditions, protective put (PP) and synthetic put (SP) yield identical payoffs and have the same cost. In practice, there are several important differences between the two strategies. On the one hand, PP seems to be an easy and uncomplicated strategy to implement, but the unavailability of listed options with desired maturities and strike prices are major issues. SP strategies, on the other hand, can suffer from obstacles like high transaction costs and jumps in stock prices.
Author: Philippe Bertrand Publisher: ISBN: Category : Languages : en Pages :
Book Description
Portfolio insurance allows investors to recover, at maturity, a given percentage of their initial capital. This limits downside risk in falling markets and allows some participation in rising markets. Therefore, these properties prove the importance of such portfolio strategies. The two standard portfolio insurance methods are the Option Based Portfolio Insurance (OBPI) and the Constant Proportion Portfolio Insurance (CPPI).The paper analyzes and compares their performances and risk characteristics by means of various criteria such as some of their quantiles. Their dynamic hedging properties are also examined in the Black and Scholes framework. In particular, the paper shows that the insured percentage of the initial capital plays a key role. It isalso proved that OBPI is a generalized CPPI.
Author: Jean-Luc Prigent Publisher: ISBN: Category : Languages : en Pages : 12
Book Description
We compare the performances of the two standard portfolio insurance methods: the Option Based Portfolio Insurance (OBPI) and the Constant Proportion Portfolio Insurance (CPPI), when the volatility of the stock index is stochastic. In this framework, we provide a quite general formula for the CPPI portfolio value. We use criteria such as comparison of payoffs functions at maturity and various quantiles. We emphasize in particular the role of the insured percentage of the initial investment.
Author: Marcos Escobar Publisher: ISBN: Category : Languages : en Pages :
Book Description
Portfolio insurance strategies that ensure a certain minimum portfolio value or floor such as the Constant Proportion Portfolio Insurance (CPPI) and the Option-based Portfolio Insurance (OBPI) are economically important and widely spread among the banking and insurance industries. In distress and volatile market environments, investors such as pension funds have a need to insure their portfolios against downside risk in order to meet certain future payments or liabilities. Non-anticipated shocks or negative interest rates, jumps, crashes or overnight trading restrictions in stock prices could drop pension fund portfolios below desired levels (present value of pension obligations) making them underfunded with pension assets to pension liabilities ratio below 100%. In particular within the current low interest rate environment, a high number of pension funds happen to be underfunded which is a severe practical problem. Because of such scenarios there is a need for an investment strategy which covers both the case of funded and underfunded portfolios. This article introduces a novel strategy which generalizes the CPPI approach. It has the overall target of guaranteeing the investment goal or floor while participating in the performance of the assets and limiting the downside risk of the portfolio at the same time. We show that the strategy accounts for behavioral aspects of the investor such as distorted probabilities, a risk-averse behavior for gains, and a risk-seeking behavior for losses. The proposed strategy turns out to be optimal within the Cumulative Prospect Theory (CPT) framework by Tversky and Kahneman (1992).
Author: Hubert Dichtl
Author: Hubert Dichtl
Author: Cheng-Few Lee
Author: Benjamin Hamidi
Author: Ralf Hohmann
Author: Lalatendu Misra
Author: Yu Zhu
Author: Felix Lütjen
Author: Philippe Bertrand
Author: Jean-Luc Prigent
Author: Marcos Escobar